As an example, we describe the HEROSumm (HiErarchical queRy focused Order-aware multi-document) model [1]} which extends the baseline summarizer [2]}.
Like the baseline summarizer, HEROSumm uses a encoder-decoder architecture based on a hierarchical Transformer model.
HEROSumm differs from the baseline in that the former introduces two new components in its encoder modules to incorporate \(Q\)  for summary generation: a query encoder, and a document ordering component that ranks documents in \(\mathcal {D}\)  based on their relevance to \(Q\) . The encoder of HEROSumm is illustrated in Figure REF . HEROSumm consists of the following components.
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